Implementation of Optimised Wireless Sensor Network Using Cluster Architecture

In the research, LixMnyNiz was obtained by co-precipitation method according to the capacity limitation characteristics of positive electrode material of lithium ion battery, and then Li-[LixMnyNiz]O2 was obtained with lithium containing compounds. By using the generated positive electrode material, the electrode plate is made and the battery is assembled. The battery is used on the photoelectric sensor node. In the design of photoelectric sensor node, the power supply adopts the battery designed in this research. CC2530 chip was used for the controller module of the sensor, and the photoelectric sensor BH1750SVI and sfh3410-2 were included. After the sensor node is designed, the communication extension node, interference source module, mobile carrier module and data analysis module were further elaborated, so as to realize the construction of photoelectric sensor network. In the experimental test, electrochemical test was conducted on the obtained lithium-rich anode material. The specific capacity of the material’s first discharge could reach 227 mAh/g, and the capacity of the material after repeated cycles could be maintained at more than 80%, but the performance of the multiplying ratio needed to be further improved. In the node power test, the traditional battery sensor node was compared with the sensor node proposed in this research. The energy consumption of the latter is 10% lower than that of the former, which indicated that the improved battery wireless sensor node proposed in this research can reduce the power consumption of the sensor network.

Hybrid based cluster head selection for maximizing network lifetime and energy efficiency in WSN

A sensor node has a limited radio range to subsequently cover a limited geographical area. In real-world setting, it is not always possible to have a single-hop wireless network. Most of the wireless network architecture may be flat or clustered with multi-hop routing. This research work simulated an adaptive multi-hop routing sensor network with different barrier levels for the sensor’s environment factor Alpha, so as to make an optimal use of the node’s battery power. By implementing a multilevel Alpha barrier in a sensor network, a significant amount of power can be saved in terms of battery power, which leads to a maximized network lifetime (MNLT).KeywordsMulti-hopAlphaFlat architectureClustered architectureMNLT

Proposed wireless sensor node is a highly flexible and programmable system on chip (PSoC) architecture along with integrated RF radio chip, which can be adapted to any IEEE 802.15.4 standard based protocol, working at the band of 2.4GHz.This can be accompanied by the RF antenna matched with the interface circuit for various kinds of sensors and peripherals to form a wireless sensor node.This can be very well used to form a wireless sensor network in different domains.This proposed methodology can be used for specific application for improving the WSN stability and performance.This article will mainly present the design of wireless sensor nodes based on PSoC and CyFi radio chip, including the application specific antenna and hardware design for the system on chip for the sensor node and the simple introduction of the application domain.The proposed nodes are used with a special antenna and application based protocol for communication.This design has a better power handling and performing capacity.Further, we have implemented this for the wireless sensor node as well.

Network lifetime play a vital role in setting up an energy efficient wireless sensor network. The lifetime of the network can be improved by efficient deployment and scheduling of the sensor nodes inside the network. In this paper, on the basis of mathematically calculated upper bound lifetime of the network, the sensor nodes are efficiently deployed by using Simulated Annealing and Particle Swarm Optimization with pre-specified sensing range of the sensor nodes and on the second fold the sensor nodes are efficiently scheduled by applying the Simulated Annealing and Dempster Shafer Theory. The overall objective of this paper is to find the optimized location and schedule for sensor nodes. The comparative study shows that the simulated annealing and particle swarm optimization algorithms performs better for sensors deployment. Simulated annealing and Dempster Shafer theory achieves the goal to provide the different schedules with high efficiency.

A Wireless Sensor Network (WSN) is an ad-hoc wireless network formed of spatially distributed autonomous sensor nodes which possess the ability of performing computations, communication & executing different sensing tasks. The design & development of wireless sensor nodes is carried out using Bluetooth as wireless networking technology. The use of Bluetooth helps to utilise many features of Bluetooth enabled devices, which could be used as an infrastructure gateways, actuators or user interfaces. A modular design approach is adapted for design & development of wireless sensor node thus making it easy to add, remove or modifying the sensor with much shorter development cycles while also supporting WSN-behavior in terms of power consumption & node operational lifetime. WSN architecture supports different network topologies like Star, mesh & hybrid Star-mesh network. An embedded wireless sensor node is designed & successfully tested for two different Star network formations.

This paper identifies the major challenges faced in designing energy efficient wireless sensor networks. It was shown that energy optimization must be done at all levels including network, sensor node, and powering methods. A specific procedure for designing free space optics remote powering was described and the use of free space optics in wireless sensor network communication has been investigated.

This paper presents a smart water management system using the microcontroller ZR16S08 as IoT solution, for water distribution support and losses prevention. The system operates through the smart monitoring of the water flow in pipes of the water distribution network, aiming to ensure quality of the water supply, knowing that water losses characterize one of the great problems in the world, as pipe holes may be open doors to water contaminants. As an alternative to circumvent this issue, a series of experiments were taken to create a network of sensors capable of monitoring water pipes in real time. Adopting criteria such as low consumption and low cost, the use the ZR16S08 microcontroller in the design of wireless sensor nodes that will be coupled in the water pipes was adopted. Complementing the system, a central processing unit, composed of a Raspberry Pi microcomputer, manages the traffic of the information collected by the sensor nodes and routes it to a web server. All data addressed by the central unit are available on-line by means of a supervisory platform. Considering the size of the sensor nodes, their power consumption, and regulatory issues, a link between the sensor nodes, operating at a frequency of 433 MHz, was defined. Preliminary results show the effectiveness of the proposed architecture for sensor nodes, allowing application for the monitoring of water and controlling losses.

A wireless pressure sensor node design method and realization is put forward aiming at problems of dynamic pressure test in the hermetic cavity or cabin, such as high wiring difficulty and influence on air flow field. Dynamic gauge pressure signal is transmitted by a wireless sensor node in consideration of temperature affection factors. The sensor node is mainly composed of gauge and atmospheric pressure, temperature sensor, signal acquisition and modulation module, wireless RF module, data memory, lithium battery. On the basis of the above, the prototype is developed. The effectiveness and reliability of the wireless pressure sensor node are verified in means of sea trial test.

Target detection and classification is very crucial in wireless sensor network for outdoor security applications. This paper presents a novel concept to detect and further discriminate dynamic objects (persons and vehicles) in WSN using geophones that work as dynamic presence detectors in a given field of interest. The basic concept to detect and classify a target lies in the idea to consider an individual footstep of a person and/or motion of a vehicle detects as an event in the detection range of the geophone. In an on-going project, the design of a wireless geophone sensor node is implemented. This design is based on high processing Gumstix Overo Fire Computer-On-Module that is used for high performance and has built-in wireless capabilities. A high resolution analog-to-digital converter is integrated to the module to acquire data from geophone. The raw data is processed on the sensor node to detect and classify a target. The adaptive wavelet denoising algorithm is applied in real-time to extract a target signal from the real noisy environments. This algorithm adjusts the threshold based on the energy of the wavelet series coefficients. Timestamps of the events are extracted using event detection method. These events are used to classify a target on a node level.

In order to solve the problems that ever wireless sensor nodes' energy consumption is high and solar-powered wireless nodes are greatly influenced by the weather and the system is not stable, comprehensive utilization of solar energy power supply technology, sensor technology and wireless communication technology, this paper designs a new type of wireless sensor nodes, which is powered by solar energy. The wireless sensor nodes which is supplied by solar energy, solving the problem of the energy consumption of sensor nodes effectively. After tested, it has simple operation, high reliability and it can satisfy the requirement of environmental parameter acquisition and monitoring work.

Internet of Things (IoT) is an important technique in the modern wireless telecommunications field. It is based on a collection of sensor nodes connected through wireless sensor networks (WSNs). The lifetime of this network is affected by the battery power of the connected sensor nodes. Network clustering techniques are used to improve energy consumption and extend the lifetime of the WSN. These techniques divide the sensor nodes into clusters and every cluster has a unique cluster head (CH) node. Recently, clustering-based metaheuristic techniques are used to solve this problem and find the optimal CH nodes under certain considerations such as less energy consumption and high reliability. This paper proposes a new clustering scheme for heterogeneous WSN using Coyote Optimization based on a Fuzzy Logic (COFL) algorithm. It uses the coyote optimization algorithm (COA) in conjunction with fuzzy logic (FL) system to reinforce and balance the clustering process for increasing the wireless network lifetime and reducing energy consumption. FL based clustering is adapted to determine a tentative set of CHs. The output of the FL is added as a solution within the initial solutions of the COA. Furthermore, a new fitness function has been adapted to minimize the total intra-cluster distance between each CH node and its cluster members and minimize the inter-cluster distance between the CHs nodes and the base station. An extensive simulation with three different scenarios is performed. The performance of the proposed COFL algorithm is compared with the well-known algorithms; namely low-energy adaptive clustering hierarchy protocol (LEACH) and stable election protocol (SEP) as traditional protocols and also coyote optimization algorithm (COA), grey wolf optimization (GWO), and particle swarm optimization (PSO). The COFL algorithm outperforms other algorithms in terms of alive node analysis, energy consumption, throughput, and central tendency measurements for alive nodes and normalized energy.

A large number of potential applications for Wireless Sensor and Actuator Networks (WSAN) have yet to be embraced by industry despite high interest amongst academic researchers. This is due to various factors such as unpredictable costs related to development, deployment and maintenance of WSAN, especially when integration with existing IT infrastructure and legacy systems is needed. Service-Oriented Architecture (SOA) is seen as a promising technique to bridge the gap between sensor nodes and enterprise applications such as factory monitoring, control, and tracking systems where sensor data is used. To date, research efforts have focused on middleware software systems located in gateway devices that implement standard service technology, such as Devices Profile for Web Services (DPWS), for interacting with the sensor network. This paper takes a different approach-deploying interoperable Simple Object Access Protocol (SOAP)-based web services directly on the nodes and not using gateways. This strategy provides for easy integration with legacy IT systems and supports heterogeneity at the lowest level. Twofold analysis of the related overhead, which is the main challenge of this solution, is performed; Quantification of resource consumption as well as techniques to mitigate it are presented, along with latency measurements showing the impact of different parts of the system on system performance. A proof-of-concept application using Mulle-a resource-constrained sensor platform-is also presented.

Sensors have a strong connection to the real world, which sets them apart from conventional networks in a major way. Through the use of a variety of sensing devices as well as the processing of raw data, sensor networks may detect & monitor physical phenomena occurring in the locations/regions where even the sensors are located or deployed. Physical phenomena linked with geographic locations/regions are much more important to users of wireless sensor networks over raw data from individual sensor nodes. Geospatial information is becoming more important in sensor networks and applications, and sensor nodes having GPS signal receivers become more widely available. Sensor nodes may also be located without GPS using a variety of localization methods. A location-aware sensor network is now possible thanks to these recent technological advancements. To address the issue of estimating the location and position among wireless sensor nodes, new approaches, techniques, and algorithms must be created. In order to achieve this goal, In this Paper, we are proposing a Distance Vector Hop (DV-Hop) algorithm that Significantly decreases the average of localization error of sensor nodes and which is a solution for localizing nodes having few adjacent anchors. simulation results prove that the proposed algorithm substantially reduces the average of localization error of sensor nodes

Efficient sensor node deployment is extremely important in wireless sensor networks. It earns great practical meanings through using fewer sensor nodes as far as possible to satisfy different requirements such as the requirement on coverage and overcoming the potential sensor node failures and the adverse influence from the environment. We propose an efficient approach for the deployment of sensor nodes in wireless networks, termed as EDSNDA, which is excellent in taking both the requirements of sensor coverage and network connectivity into consideration when minimizing the number of necessary sensor nodes to the best of its ability. We proposed a new coverage model of sensor node. Based on the sensor coverage model, we establish four dynamic programming models in four different practical situations, respectively. The algorithms are then proposed which are used for solving the corresponding dynamic programming models. The validity of the method is justified by simulation studies in which the method is compared with the current representative methods. The simulation results show that our method performs better than the other ones with fewer sensor nodes, better coverage and network connectivity result in the same circumstance.